DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Objections
Claim 14 objected to because of the following informalities: Referring to claim 14, “computer resources” is understood to refer to “computing resources”. Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim 18 is rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. Claim 15 already claims that the second software programs are caused to be performed and that they are done so on the basis of the generated score, which is a score of past performance of the computing resources. As such, claim 18 does not appear to further limit claim 15. Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Referring to claim 1, at step 1, if no statutory category rejection was given above, then the claims have been determined to have a statutory category.
At step 2a, prong one, as emphasized, there is disclosed a generic processor implementing a first program for generating a score using a function applied to data and then performing a second program based on the generated score. Claim 1 recited, “A processor, comprising: one or more circuits to: cause one or more first software programs to generate a score of past performance of one or more computing resources based, at least in part, on a decay function applied over a period of time corresponding to a time series of events associated with the past performance of the one or more computing resources during the period of time such that, to generate the score, more recent events of the time series of events that occurred during the period of time are weighted more heavily than less recent events of the time series of events that occurred during the period of time according to the decay function; and cause, based at least in part on the generated score, one or more second software programs to be performed using the one or more computing resources.”
The limitation of generating a score, as crafted, are processes that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of additional elements that do not integrate the judicial exception into a practical application. That is, nothing in these claim elements as emphasized precludes the step from practically being performed in the mind, possibly with the aid pen and paper. For example, these steps perform steps of observation, evaluation, judgment, or opinion.
At step 2a, prong two, this judicial exception is not integrated into a practical application. In particular the claim additionally recites a generic computer and performing a software program.
The computer is recited at a high level of generality. The computer is used to perform an abstract idea, as discussed above in Step 2A, Prong One, such that it amounts to no more than mere instructions to apply the exception using a generic computer. See MPEP 2106.05(f).
The limitations of performing a software program provides nothing more than mere instructions to implement an abstract idea on a generic computer. See MPEP 2106.05(f).
Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application, and the claim is directed to the judicial exception. As claimed, this merely performs analysis on data and does an action responsively.
At step 2b, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, there are the additional elements of a generic computer and performing a software program.
The limitations regarding use of a computer amounts to no more than mere instructions to apply the exception using a generic computer component. See MPEP2106.05(d), for example TLI Communications, Flook, Alice Corp, and Versata.
The recitation of performing a software program are at best mere instructions to “apply” the abstract ideas, which cannot provide an inventive concept. See MPEP 2106.05(f). See MPEP 2106.05(g) In re Brown and Ameranth and MPEP 2106.05(d) Flook.
Even when considered in combination, these additional elements represent mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept.
Further referring to claim 2-6, this performs additional observation, evaluation, judgment, or opinion.
Referring to claim 7, see rejection of claim 1 above.
Further referring to claim 8-12, this performs additional observation, evaluation, judgment, or opinion..
Further referring to claim 13, at step 2a prong one, the claim recites scheduling the software program on a node, wherein a node may be a GPU. Scheduling as crafted, are processes that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of additional elements that do not integrate the judicial exception into a practical application. That is, nothing in these claim elements as emphasized precludes the step from practically being performed in the mind, possibly with the aid pen and paper. For example, these steps perform steps of observation, evaluation, judgment, or opinion.
At step 2a, prong two, this judicial exception is not integrated into a practical application. In particular the claim additionally recites a generic compute, albeit with additional detail in the form of a GPU. Notably a generic computer already has a resource “node”.
The computer is recited at a high level of generality. The computer is used to perform an abstract idea, as discussed above in Step 2A, Prong One, such that it amounts to no more than mere instructions to apply the exception using a generic computer. See MPEP 2106.05(f). Regarding a GPU in particular, see for example US 20190164328 A1 paragraph 1, US 20220172695 A1 paragraph 3, US 20220366628 A1 paragraph 4, US 20210158470 A1 paragraph 3, US 20120001925 A1 paragraph 12.
Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application, and the claim is directed to the judicial exception. As claimed, this merely again has a generic computer perform an operation, here, potentially by a GPU.
Further referring to claim 14, prioritization is observation, evaluation, judgment, or opinion.
Referring to claim 15, see rejection of claim 1 above.
Further referring to claims 16-20, see rejection of claims 5, 8, 9, 10, 12 above.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 4-10, 14-18, 20 is/are rejected under 35 U.S.C. 102a2 as being anticipated by US11599442 to Biller et al.
Referring to claim 1, Biller discloses a processor, comprising: one or more circuits to:
cause one or more first software programs to generate a score of past performance of one or more computing resources based, at least in part, on a decay function applied over a period of time corresponding to a time series of events associated with the past performance of the one or more computing resources during the period of time such that, to generate the score, more recent events of the time series of events that occurred during the period of time are weighted more heavily than less recent events of the time series of events that occurred during the period of time according to the decay function (Abstract, “In a present invention embodiment, time series data is received including information pertaining to a corresponding attribute of monitored activity on a processing device. An upper bound of the time series data is determined based on a weighted combination of a prior upper bound and a current value derived from the time series data. Greater weight is provided to greater values in the time series data based on an exponent applied to the prior upper bound and the current value and an effect of older values in the time series data decays over time based on a smoothing factor applied to exponential values of the prior upper bound and the current value. The upper bound is applied to a profile of an entity, and abnormal activity on the processing device is detected based on a comparison of the upper bound to a corresponding bound of the profile.” Further, from line 27 of column 4, “The modules of present invention embodiments (e.g., stream processing module 116, security module 120, interface module 122, collection agent 140, etc.) may include one or more modules or units to perform the various functions of present invention embodiments described below. The various modules (e.g., stream processing module 116, security module 120, interface module 122, collection agent 140, etc.) may be implemented by any combination of any quantity of software and/or hardware modules or units, and may reside within memory 135 of the server, database server, and/or client systems for execution by a corresponding processor 115.”); and
cause, based at least in part on the generated score, one or more second software programs to be performed using the one or more computing resources (From line 32 of column 13, “When an anomaly is identified as determined at operation 525, security module 120 initiates or performs an appropriate action at operation 530. For example, notifications may be sent to organizations or users (e.g., administrators of database 145, etc.) indicating a potential security issue (e.g., monitored activity does not correspond to normal behavior, etc.). Further, controls may be generated and applied to deny and/or terminate access for the entity (e.g., user, application, machine or device, component, etc.) corresponding to the abnormal behavior. In addition, collection agent 140 may be configured or directed to capture other events and generate event streams pertaining to the anomaly for a closer examination. For example, the collection agent may be configured to capture events based on a larger set of characteristics to analyze data streams with details pertaining to the anomaly. Thus, the behavior may be monitored, and abnormal behavior detected, in real-time to address security issues.”).
Referring to claim 4, Biller discloses wherein the one or more circuits cause the one or more second software programs to be performed on the one or more computing resources based, at least in part, on a label assigned to the one or more computing resources (From line 32 of column 13, “When an anomaly is identified as determined at operation 525, security module 120 initiates or performs an appropriate action at operation 530. For example, notifications may be sent to organizations or users (e.g., administrators of database 145, etc.) indicating a potential security issue (e.g., monitored activity does not correspond to normal behavior, etc.). Further, controls may be generated and applied to deny and/or terminate access for the entity (e.g., user, application, machine or device, component, etc.) corresponding to the abnormal behavior. In addition, collection agent 140 may be configured or directed to capture other events and generate event streams pertaining to the anomaly for a closer examination. For example, the collection agent may be configured to capture events based on a larger set of characteristics to analyze data streams with details pertaining to the anomaly. Thus, the behavior may be monitored, and abnormal behavior detected, in real-time to address security issues.”).
Referring to claim 5, Biller discloses wherein the one or more first software programs score past performance based, at least in part, on one or more events stored in a time series database system (Abstract, “In a present invention embodiment, time series data is received including information pertaining to a corresponding attribute of monitored activity on a processing device. An upper bound of the time series data is determined based on a weighted combination of a prior upper bound and a current value derived from the time series data. Greater weight is provided to greater values in the time series data based on an exponent applied to the prior upper bound and the current value and an effect of older values in the time series data decays over time based on a smoothing factor applied to exponential values of the prior upper bound and the current value. The upper bound is applied to a profile of an entity, and abnormal activity on the processing device is detected based on a comparison of the upper bound to a corresponding bound of the profile.”).
Referring to claim 6, Biller discloses wherein the one or more circuits cause the one or more second software programs to be performed on the one or more computing resources based, at least in part, on one or more attribute values of the one or more computing resources exceeding a threshold value (From line 5 of column 13, “Once the bounds of the time series data (e.g., representing activity load (or density), etc.) are determined for corresponding event streams, security module 120 evaluates the bounds for the various event streams against profiles of entities associated with the activity (e.g., user, application, machine or device, component, etc.) indicating valid or normal corresponding behaviors at operation 520. For example, entity accesses may be monitored over a time window and event streams (or time series data) indicating occurrence of corresponding events may be produced based on activities. The events may correspond to various events as described above (e.g., use of specific SQL or other commands (e.g., verbs, etc.), Internet Protocol (IP) addresses, applications, database tables accessed, databases accessed, hours of the day of access, etc.). The bounds for each event stream may be determined as described above and used to form a profile for an entity (e.g., user, application, machine or device, component, etc.). For example, the profile may include bounds for various events (e.g., use of specific SQL or other commands (e.g., verbs, etc.), Internet Protocol (IP) addresses, applications, database tables accessed, databases accessed, hours of the day of access, etc.). The approximated bounds of monitored activity data may be compared to bounds of events within a profile for a corresponding entity to determine the presence of security anomalies (e.g., when approximated bounds of the monitored activity are outside the bounds of the profile, etc.).”).
Referring to claim 7, see rejection of claim 1 above.
Referring to claim 8, Biller discloses wherein the one or more first software programs score past performance of the one or more computing resources based, at least in part, on aggregating one or more events of the one or more computing resources over periods of time (Abstract, “In a present invention embodiment, time series data is received including information pertaining to a corresponding attribute of monitored activity on a processing device. An upper bound of the time series data is determined based on a weighted combination of a prior upper bound and a current value derived from the time series data. Greater weight is provided to greater values in the time series data based on an exponent applied to the prior upper bound and the current value and an effect of older values in the time series data decays over time based on a smoothing factor applied to exponential values of the prior upper bound and the current value. The upper bound is applied to a profile of an entity, and abnormal activity on the processing device is detected based on a comparison of the upper bound to a corresponding bound of the profile.”).
Referring to claim 9, Biller discloses wherein the one or more first software programs score past performance of the one or more computing resources based, at least in part, on a weighted average of events over a time period (From line 1 of column 12, “A weighted exponential generalized mean with a high exponent is applied between the history portion and the current value portion of the exponential smoothing. For example, the history portion and current portion of the exponential smoothing are each raised to the power of an exponent p, and the p.sup.th root of the sum of the exponential history and current portions weighted by the smoothing factor is determined to produce the upper bound. This provides a smoothing average on time series data with a higher weight for higher values (according to the exponent p). In this manner, a resulting function, M(n), provides an estimation for the upper bound of time series data, but the influence of older values (or older event occurrences) decays over time. This estimation is provided with very low computational effort and with no additional storage required (except for the previous value of the function). Accordingly, a present invention embodiment determines the bound as the data is streamed in real-time.”).
Referring to claim 10, Biller discloses wherein the past performance is scored based, at least in part, on the decay function applied to one or more events of the one or more computing resources for a predetermined window of time in the time series (From line 1 of column 12, “A weighted exponential generalized mean with a high exponent is applied between the history portion and the current value portion of the exponential smoothing. For example, the history portion and current portion of the exponential smoothing are each raised to the power of an exponent p, and the p.sup.th root of the sum of the exponential history and current portions weighted by the smoothing factor is determined to produce the upper bound. This provides a smoothing average on time series data with a higher weight for higher values (according to the exponent p). In this manner, a resulting function, M(n), provides an estimation for the upper bound of time series data, but the influence of older values (or older event occurrences) decays over time. This estimation is provided with very low computational effort and with no additional storage required (except for the previous value of the function). Accordingly, a present invention embodiment determines the bound as the data is streamed in real-time.”).
Referring to claim 14, Biller discloses, wherein the one or more of the computer resources with past performance scores that exceed a threshold value are prioritized to perform the one or more second software programs and the one or more of computing resources with past performance scores that are below the threshold value are deprioritized (From line 32 of column 13, “When an anomaly is identified as determined at operation 525, security module 120 initiates or performs an appropriate action at operation 530. For example, notifications may be sent to organizations or users (e.g., administrators of database 145, etc.) indicating a potential security issue (e.g., monitored activity does not correspond to normal behavior, etc.). Further, controls may be generated and applied to deny and/or terminate access for the entity (e.g., user, application, machine or device, component, etc.) corresponding to the abnormal behavior. In addition, collection agent 140 may be configured or directed to capture other events and generate event streams pertaining to the anomaly for a closer examination. For example, the collection agent may be configured to capture events based on a larger set of characteristics to analyze data streams with details pertaining to the anomaly. Thus, the behavior may be monitored, and abnormal behavior detected, in real-time to address security issues.”).
Referring to claim 15-18, 20, see rejection of claim 1, 5, 8-10 above.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Biller as applied to claim 1 above, and further in view of US20220318082 to Slinger et al.
Referring to claim 2, Although Biller does not specifically disclose wherein the one or more computing resources are categorized using a fitness score band of a plurality of fitness score bands, wherein each fitness score band of the plurality of fitness score bands comprises a threshold value that is configurable, this is known in the art. In a related field of computing, an example of this is shown by Slinger, from paragraph 32, “To assist the user and visually elevate awareness of specific scores, color schemes or other visual techniques may be used. For example, scores within defined ranges may be colored green to indicate a satisfactory condition, yellow to indicate a cautionary condition, and red to indicate an anomaly. Such visual representations may also be helpful in providing an overall sense of a condition of a monitored system, including trending conditions. For example, the displayed grid may primarily have green values, or may primarily have red values, or may be trending from being primarily green to primarily yellow and then red.” It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use such bands because, as disclosed by Slinger, this may be used to assist the user and elevate awareness.
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Biller as applied to claim 1 above, and further in view of Official notice (sampling rates).
Referring to claim 3, Biller discloses past performance of the one or more computing resources is generated based, at least in part, on a period of time. For example, from line 59 of column 2 of Biller, “A present invention embodiment employs exponential smoothing and an exponential generalized mean to maintain one or more bounds of time series data. This minimizes storage since the number of values maintained for the determination is minimal, and provides greater weight to recent values while gradually removing effects of older values. In other words, values of recent events are remembered, but older events in an event history are gradually forgotten. The minimization of storage further minimizes run time for updating training data of a statistical model (e.g., for analytics, etc.) and performing real-time analysis.” Further, from line 6 of column 16, “The event stream may be processed in any manner to determine or produce data for a behavior or activity attribute (e.g., weighted or smoothed mean, etc.). Alternatively, the collection agent may capture data for the behavior or activity attribute. The data for the activity attribute may span in any degree suitable for analysis (e.g., continuous over time, any suitable time intervals between data points for the analysis, etc.). The bounds may be approximated based on various combinations of a weighted or exponential mean and exponential smoothing. The smoothing factor of the bound approximation may be set to any desired values within any value ranges to distribute weight to recent and older data. The smoothing factor of the bound approximation may be selected and/or tuned based on any desired factors (e.g., time, half-life, etc.). The exponent of the bound approximation may set to any desired values within any value ranges to distribute weight to greater and lesser values. The exponent of the bound approximation may be selected and/or tuned based on any desired factors (e.g., a range of resulting values to values of the time series data, may be reduced by a decrement over time, etc.).” Although Biller does not explicitly disclose a ratio of a sample rate, sampling rates are very well known in the art. In a related field of computing, examiner takes official notice for a sampling rate. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use a sampling rate because sampling has lower costs and faster data collection.
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Biller as applied to claim 7 above, and further in view of Official notice (transient failures).
Referring to claim 11, Biller discloses wherein the past performance is based, at least in part, on transient failures, these are very well known in the art. In a related field of computing, examiner takes official notice for transient failures. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include transient failures because such failures may happen on virtually any system, and Biller in particular is interested in any event which may detect both normal and abnormal behavior (from line 12 of column 10, “Initially, a database server system 130 (FIG. 1) may receive various requests from client systems 114 to access data from database system 145. The database server system processes the requests to retrieve the requested data from database system 145. Collection agent 140 of the database server system monitors activity and generates one or more event streams in real-time at operation 505. Each event stream may include time series values indicating occurrence of a corresponding event and an associated time (e.g., a timestamp, etc.). The corresponding event may be associated with an attribute of the monitored activity. For example, the event streams may indicate an attribute of a frequency of occurrence of the corresponding events over time which can be used as patterns to detect normal and abnormal behavior.”).
Claim(s) 12, 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Biller as applied to claim 7, 15 above, and further in view of US 20180107528 to Vizier et al.
Referring to claim 12, although Biller does not specifically disclose the past performance is scored based, at least in part, on one or more severity scores of events, this is known in the art. In a related field of computing, an example of this is shown by Vizier. From paragraph 19, “ In order to address the aforementioned aspects related to event detection and management, according to examples, an aggregation based event identification apparatus and a method for aggregation based event identification are disclosed herein. For the apparatus and method disclosed herein, machine learning and other techniques as disclosed herein may be used to ascertain unique events that exist in an associated system. For example, an events collection module may receive a plurality of events (e.g., an event stream of source events from a source system), and ascertain unique events (i.e., event types as described herein) from the plurality of received events by clustering. Each event type may represent a cluster of events of a same (or similar) type. Thus, an event type may represent a plurality of same (or similar) events in the event stream. The event types may be aggregated to generate a reduced number of the source events. An event weighting module may analyze, for each of the reduced number of the source events, a priority characteristic (e.g., based on severity or known keywords), an abnormal behavior characteristic (e.g., based on deviation from a normal distribution), and/or a tagged characteristic (e.g., based on tagging by subject matter expert (SME) input with respect to relevant events or event types in earlier cases). The event weighting module may assign, based on the analysis for each of the reduced number of the source events, a priority characteristic weight, an abnormal behavior characteristic weight, and/or a tagged characteristic weight to each of the reduced number of the source events.” It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include severity in weighting because, as shown by Vizier, this allows for event detection and management.
Referring to claim 19, see rejection of claim 12 above.
Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Biller as applied to claim 7 above, and further in view of US 20180336065 A1 to Martin et al.
Referring to claim 13, Biller discloses wherein to cause the one or more second software programs to be performed includes to schedule the one or more second software programs on the one or more computing resources, wherein the one or more computing resources include one or more nodes (From line 32 of column 13, “When an anomaly is identified as determined at operation 525, security module 120 initiates or performs an appropriate action at operation 530. For example, notifications may be sent to organizations or users (e.g., administrators of database 145, etc.) indicating a potential security issue (e.g., monitored activity does not correspond to normal behavior, etc.). Further, controls may be generated and applied to deny and/or terminate access for the entity (e.g., user, application, machine or device, component, etc.) corresponding to the abnormal behavior. In addition, collection agent 140 may be configured or directed to capture other events and generate event streams pertaining to the anomaly for a closer examination. For example, the collection agent may be configured to capture events based on a larger set of characteristics to analyze data streams with details pertaining to the anomaly. Thus, the behavior may be monitored, and abnormal behavior detected, in real-time to address security issues.”).
Although Biller does not specifically disclose wherein the one or more nodes include one or more graphics processing units (GPUs) to perform at least part of the one or more second software programs, including GPUs which may perform an assigned operation is known in the art. In a related field of computing, an example of this is shown by Martin, from paragraph 24, “Thus, as shown in FIG. 3, processor time on the CPU 7 must be respectively allocated 41 to the two rendering tasks for performing the necessary CPU (host processor) processing on the CPU for the application rendering 30 and the time warp slice rendering 31. Correspondingly, the two rendering tasks must also be appropriately provided to the GPU driver that is executing in the kernel space 39 on the host processor for appropriate scheduling 40 to the GPU 2 for those rendering tasks to be performed. There is therefore a need to be able to control and synchronise the timing of the execution of the relevant rendering task processing on the CPU 7 for both the application rendering 30 and the time warp slice rendering 31 so that those rendering operations can be completed by the GPU at and by the appropriate time to allow the desired frames to be displayed.” It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include a GPU because, as shown by Martin, this allows for the execution a GPU specific task such as rendering.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See notice of references cited.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GABRIEL L CHU whose telephone number is (571)272-3656. The examiner can normally be reached weekdays 8 am to 5 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ashish Thomas can be reached at (571)272-0631. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/GABRIEL CHU/ Primary Examiner, Art Unit 2114
